{"_id":"58f5d59402c293230028f0a2","__v":0,"githubsync":"","user":"5767bc73bb15f40e00a28777","version":{"_id":"55faf11ba62ba1170021a9aa","project":"55faf11ba62ba1170021a9a7","__v":45,"createdAt":"2015-09-17T16:58:03.490Z","releaseDate":"2015-09-17T16:58:03.490Z","categories":["55faf11ca62ba1170021a9ab","55faf8f4d0e22017005b8272","55faf91aa62ba1170021a9b5","55faf929a8a7770d00c2c0bd","55faf932a8a7770d00c2c0bf","55faf94b17b9d00d00969f47","55faf958d0e22017005b8274","55faf95fa8a7770d00c2c0c0","55faf96917b9d00d00969f48","55faf970a8a7770d00c2c0c1","55faf98c825d5f19001fa3a6","55faf99aa62ba1170021a9b8","55faf99fa62ba1170021a9b9","55faf9aa17b9d00d00969f49","55faf9b6a8a7770d00c2c0c3","55faf9bda62ba1170021a9ba","5604570090ee490d00440551","5637e8b2fbe1c50d008cb078","5649bb624fa1460d00780add","5671974d1b6b730d008b4823","5671979d60c8e70d006c9760","568e8eef70ca1f0d0035808e","56d0a2081ecc471500f1795e","56d4a0adde40c70b00823ea3","56d96b03dd90610b00270849","56fbb83d8f21c817002af880","573c811bee2b3b2200422be1","576bc92afb62dd20001cda85","5771811e27a5c20e00030dcd","5785191af3a10c0e009b75b0","57bdf84d5d48411900cd8dc0","57ff5c5dc135231700aed806","5804caf792398f0f00e77521","58458b4fba4f1c0f009692bb","586d3c287c6b5b2300c05055","58ef66d88646742f009a0216","58f5d52d7891630f00fe4e77","59a555bccdbd85001bfb1442","5a2a81f688574d001e9934f5","5b080c8d7833b20003ddbb6f","5c222bed4bc358002f21459a","5c22412594a2a5005cc9e919","5c41ae1c33592700190a291e","5c8a525e2ba7b2003f9b153c","5cbf14d58c79c700ef2b502e"],"is_deprecated":false,"is_hidden":false,"is_beta":true,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"category":{"_id":"58f5d52d7891630f00fe4e77","project":"55faf11ba62ba1170021a9a7","version":"55faf11ba62ba1170021a9aa","__v":0,"sync":{"url":"","isSync":false},"reference":false,"createdAt":"2017-04-18T08:58:21.978Z","from_sync":false,"order":39,"slug":"data-cruncher","title":"DATA CRUNCHER"},"parentDoc":null,"project":"55faf11ba62ba1170021a9a7","metadata":{"title":"","description":"","image":[]},"updates":[],"next":{"pages":[],"description":""},"createdAt":"2017-04-18T09:00:04.539Z","link_external":false,"link_url":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":8,"body":"At the moment, Data Cruncher offers a set of predefined libraries curated by Seven Bridges bioinformaticians, which are automatically available every time an analysis is started. The list of available libraries depends on the editor you are using (**JupyterLab** or **RStudio**).\n\n## JupyterLab\n\nThe libraries are installed using **conda**, as JupyterLab supports multiple programming languages and **conda** is a language-agnostic package manager. \n\nHere is a list of libraries that are installed by default:\n\n* Python2 \\ Python3:\n    * **path.py, biopython, pymongo, cytoolz, pysam, pyvcf, ipywidgets, beautifulsoup4, sevenbridges-python, cigar, bioservices, intervaltree, appdirs, cssselect, bokeh, scikit-allel, cairo, lxml, cairosvg, rpy2**\n* R:\n    * **r-ggfortify, r, r-stringi, r-pheatmap, r-gplots, bioconductor-ballgown, bioconductor-deseq2, bioconductor-metagenomeseq, bioconductor-biomformat, bioconductor-biocinstaller, sevenbridges-r, r-xml**\n\nThe aforementioned libraries are installed on top of the libraries that are already available in [datascience-notebook](https://github.com/jupyter/docker-stacks/tree/master/datascience-notebook).\n\nYou can also install libraries directly from the notebook and use them during the execution of your analysis. For optimal performance and avoidance of potential conflicts, we recommend using **conda** when installing libraries within your analyses. However, unlike default libraries, libraries installed in that way will not be automatically available next time the analysis is started.\n\n## RStudio (beta)\nRStudio installation is based on the **rstudio/verse** image from [The Rocker Project](https://www.rocker-project.org/) and contains **tidyverse**, **devtools**, **tex** and publishing-related packages. For more information about the image, please see its [Docker Hub repository](https://hub.docker.com/r/rocker/verse). \n\nHere is a list of libraries that are installed by default:\n\n  * CRAN - **BiocManager**, **ggfortify**, **pheatmap**, **gplots**\n  * Bioconductor - **ballgown**, **DESeq2**, **metagenomeSeq**, **biomformat**, **BiocInstaller**\n  * [sevenbridges-r](https://github.com/sbg/sevenbridges-r)","excerpt":"","slug":"about-libraries-in-a-data-cruncher-analysis","type":"basic","title":"About libraries in a Data Cruncher analysis"}

About libraries in a Data Cruncher analysis


At the moment, Data Cruncher offers a set of predefined libraries curated by Seven Bridges bioinformaticians, which are automatically available every time an analysis is started. The list of available libraries depends on the editor you are using (**JupyterLab** or **RStudio**). ## JupyterLab The libraries are installed using **conda**, as JupyterLab supports multiple programming languages and **conda** is a language-agnostic package manager. Here is a list of libraries that are installed by default: * Python2 \ Python3: * **path.py, biopython, pymongo, cytoolz, pysam, pyvcf, ipywidgets, beautifulsoup4, sevenbridges-python, cigar, bioservices, intervaltree, appdirs, cssselect, bokeh, scikit-allel, cairo, lxml, cairosvg, rpy2** * R: * **r-ggfortify, r, r-stringi, r-pheatmap, r-gplots, bioconductor-ballgown, bioconductor-deseq2, bioconductor-metagenomeseq, bioconductor-biomformat, bioconductor-biocinstaller, sevenbridges-r, r-xml** The aforementioned libraries are installed on top of the libraries that are already available in [datascience-notebook](https://github.com/jupyter/docker-stacks/tree/master/datascience-notebook). You can also install libraries directly from the notebook and use them during the execution of your analysis. For optimal performance and avoidance of potential conflicts, we recommend using **conda** when installing libraries within your analyses. However, unlike default libraries, libraries installed in that way will not be automatically available next time the analysis is started. ## RStudio (beta) RStudio installation is based on the **rstudio/verse** image from [The Rocker Project](https://www.rocker-project.org/) and contains **tidyverse**, **devtools**, **tex** and publishing-related packages. For more information about the image, please see its [Docker Hub repository](https://hub.docker.com/r/rocker/verse). Here is a list of libraries that are installed by default: * CRAN - **BiocManager**, **ggfortify**, **pheatmap**, **gplots** * Bioconductor - **ballgown**, **DESeq2**, **metagenomeSeq**, **biomformat**, **BiocInstaller** * [sevenbridges-r](https://github.com/sbg/sevenbridges-r)